Systems and Methods for Data Representation in an Optical Measurement System

1 . A method comprising:

accessing, by a computing device, a model simulating light scattered by a simulated target, the model comprising a plurality of parameters;

generating, by the computing device, a set of possible histogram data using the model with a plurality of values for the parameters; and

determining, by the computing device, a set of components that represent the set of possible histogram data, the set of components having a reduced dimensionality from the set of possible histogram data.

2 . The method of claim 1 , wherein the plurality of parameters comprises at least one of an absorption coefficient or a scattering coefficient of the simulated target.

3 . The method of claim 1 , wherein:

the model comprises a modeled light source and a modeled detector for detecting the simulated light scattered by the simulated target; and

the plurality of parameters comprises a parameter representative of a distance between the modeled light source and the modeled detector.

4 . The method of claim 1 , wherein the determining the set of components comprises:

normalizing the set of possible histogram data to generate a normalized data set;

determining a covariance of the normalized data set; and

determining the set of components based on the covariance.

5 . The method of claim 1 , wherein the components comprise eigenvectors determined using principal component analysis (PCA).

6 . The method of claim 5 , wherein the set of components comprises a subset of the eigenvectors.

7 . The method of claim 1 , further comprising:

generating, by the computing device and based on arrival times of photons at a detector after the photons are scattered by a physical target, actual histogram data associated with the physical target; and

generating, by the computing device and based on the set of components, a compressed representation of the actual histogram data.

8 . The method of claim 7 , wherein the generating the compressed representation comprises determining a set of weights that define a linear combination of the set of components to represent the actual histogram data.

9 . The method of claim 7 , further comprising modifying, based on the actual histogram data, the set of components.

10 . A system comprising:

a memory storing instructions; and

a processor communicatively coupled to the memory and configured to execute the instructions to:

access a model simulating light scattered by a simulated target, the model comprising a plurality of parameters;

generate a set of possible histogram data using the model with a plurality of values for the parameters; and

determine a set of components that represent the set of possible histogram data, the set of components having a reduced dimensionality from the set of possible histogram data.

11 . The system of claim 10 , wherein the plurality of parameters comprises at least one of an absorption coefficient or a scattering coefficient of the simulated target.

12 . The system of claim 10 , wherein:

the model comprises a modeled light source and a modeled detector for detecting the simulated light scattered by the simulated target; and

the plurality of parameters comprises a parameter representative of a distance between the modeled light source and the modeled detector.

13 . The system of claim 10 , wherein the determining the set of components comprises:

normalizing the set of possible histogram data to generate a normalized data set;

determining a covariance of the normalized data set; and

determining the set of components based on the covariance.

14 . The system of claim 10 , wherein the components comprise eigenvectors determined using principal component analysis (PCA).

15 . The system of claim 14 , wherein the set of components comprises a subset of the eigenvectors.